Two-Part and Related Regression Models for Longitudinal Data

Posted: 21 Mar 2017

See all articles by V.T. Farewell

V.T. Farewell

University of Cambridge

D.L. Long

West Virginia University

B.D.M. Tom

University of Cambridge

S. Yiu

University of Cambridge

L. Su

University of Cambridge

Date Written: March 2017

Abstract

Statistical models that involve a two-part mixture distribution are applicable in a variety of situations. Frequently, the two parts are a model for the binary response variable and a model for the outcome variable that is conditioned on the binary response. Two common examples are zero-inflated or hurdle models for count data and two-part models for semicontinuous data. Recently, there has been particular interest in the use of these models for the analysis of repeated measures of an outcome variable over time. The aim of this review is to consider motivations for the use of such models in this context and to highlight the central issues that arise with their use. We examine two-part models for semicontinuous and zero-heavy count data, and we also consider models for count data with a two-part random effects distribution.

Suggested Citation

Farewell, V.T. and Long, D.L. and Tom, B.D.M. and Yiu, S. and Su, L., Two-Part and Related Regression Models for Longitudinal Data (March 2017). Annual Review of Statistics and Its Application, Vol. 4, Issue 1, pp. 283-315, 2017, Available at SSRN: https://ssrn.com/abstract=2937748 or http://dx.doi.org/10.1146/annurev-statistics-060116-054131

V.T. Farewell (Contact Author)

University of Cambridge ( email )

Trinity Ln
Cambridge, CB2 1TN
United Kingdom

D.L. Long

West Virginia University

PO Box 6025
Morgantown, WV 26506
United States

B.D.M. Tom

University of Cambridge

Trinity Ln
Cambridge, CB2 1TN
United Kingdom

S. Yiu

University of Cambridge

Trinity Ln
Cambridge, CB2 1TN
United Kingdom

L. Su

University of Cambridge

Trinity Ln
Cambridge, CB2 1TN
United Kingdom

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